Video conferencing has become more and more popular thanks to the emergence of high speed Internet and reduced prices of high quality web cameras. Wide-spread instant messaging software supports voice/video chatting, where people can view each other while talking. There are, however, privacy concerns with video conferencing. For instance, some people do not want to show their living rooms, bedrooms or offices to other people.
There are a number of approaches to overcoming the privacy issue with video conferencing. For example, some applications replace a talking face with a 3D animated avatar. It is fun to play with such effects, though the expressiveness of the avatars is often limited and cannot deliver information as rich as that conveyed by true faces. An alternative solution is to separate the foreground and background objects in the video, so that the background can be replaced by a different image or video. This would be ideal for preserving privacy while maintaining the effectiveness of the conversation, except that automatic video foreground/background segmentation is a very challenging task. In addition, human eyes are very sensitive to segmentation errors during background replacement, which demands the segmentation algorithm to be extremely accurate.
Existing approaches to preserving privacy in video conferencing are either too slow to be processed in real time, or assume a known background, or require a stereo camera pair. Few of them have achieved the efficiency, accuracy and convenience needed in real-world applications.